Class-agnostic attention module computes attention vector \(\lambda \)  (def REF ) directly from raw data, by applying fully connected and ReLU layers over video features, followed by a sigmoid function to scale attention weights to \([0,1]\) . Learning class-agnostic attention weights is used in many methods such as RPN [1]}, BG modeling [2]}, AutoLoc[3]}, CleanNet [4]}, DGAM [5]}, STPN [6]} , BaSNet [7]} , MAAN [8]}, and CMCS [9]}.
